SOTAVerified

Word Alignment

Word Alignment is the task of finding the correspondence between source and target words in a pair of sentences that are translations of each other.

Source: Neural Network-based Word Alignment through Score Aggregation

Papers

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Showing 61–70 of 551 papers

TitleStatusHype
Revitalize Region Feature for Democratizing Video-Language Pre-training of RetrievalCode1
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings—0
CL-NERIL: A Cross-Lingual Model for NER in Indian LanguagesCode0
Graph Neural Networks for Multiparallel Word Alignment—0
Improving Word Translation via Two-Stage Contrastive LearningCode1
ATOGAN:Adaptive Training Objective Generative Adversarial Network for Cross-lingual Word Alignment in Non-Isomorphic Embedding Spaces—0
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Small Model and In-Domain Data Are All You Need—0
Multilingual Sequence Labeling Approach to solve Lexical Normalization—0
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All datasetsen-esen-fres-enfr-enen-itMUSE en-deMUSE en-pt

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@184.26—Unverified
2Adv - Refine - CSLSP@181.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@182.94—Unverified
2Adv - Refine - CSLSP@182.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@183.5—Unverified
2Adv - Refine - CSLSP@183.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@183.23—Unverified
2Adv - Refine - CSLSP@182.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@181.45—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@174.08—Unverified
#ModelMetricClaimedVerifiedStatus
1Barycenter AlignmentP@184.65—Unverified